Research Assistant (Research Engineer - Machine Learning and Medical Image Analysis)
- NATIONAL UNIVERSITY OF SINGAPORE
- 17 Jan 2023
- End of advertisement period
- 16 Feb 2023
- Academic Discipline
- Engineering & Technology, Computer Science, General Engineering, Physical Sciences, Mathematics & Statistics, Physics & Astronomy
- Contract Type
- Fixed Term
- Full Time
The National University of Singapore invites applications for research assistant in the Computational Brain Imaging Group (CBIG), Centre for Translational MR Research (TMR) at the Yong Loo Lin School of Medicine. More information on the laboratory is available at https://sites.google.com/view/yeolab
Our group develops machine learning algorithms to automatically generate discoveries from large-scale brain imaging data. We seek to discover fundamental principles of brain network organization, how brain networks are organized to support cognition and how brain networks are disrupted in mental disorders.
Key attractions are access to a high-performance computing cluster as well as collaboration opportunities with an excellent network of domestic and international scientists and doctors. Appointments will be made on a two-year contract basis in the first instance, with the possibility of extension. Ideal start date is between Jan 2023 and July 2023.
Purpose of the post
The Research Assistant (RA) will work closely with the Principal Investigator, lab members, and collaborators to ensure smooth operation of computing servers/storage, efficient database management, and successful completion of research projects in the lab. The RA will be given the opportunity to spearhead his/her own project. A number of previous RAs have successfully published first-author studies and gone on to pursue graduate studies at top universities locally and overseas, including Stanford, Cornell and Oxford.
Main Duties and Responsibilities
The research assistant will support the effort in conducting cutting-edge neuroscience and machine learning research and development. He/she will have the opportunity to learn and apply state-of-the-art neuroimaging and machine learning techniques. He/she will be engaged in computing server and storage administration (with support from external vendors), website maintenance, and neuroimage processing using automatic or semi-automatic scripts, and general IT management. He/she will have the opportunity to spearhead his/her own research project.
The applicant should have:
- Bachelor’s degree or master’s degree with strong IT, engineering, computing, physics, mathematics and/or programming skills
- Excellent written, oral communication skills
- Prior system administration (Linux/Mac OS) or programming experience (e.g., python, MATLAB, shell) is a plus
- Seek organized, reliable, self-motivated individual who is able to work effectively with others and multitask efficiently
- Expected to commit for at least two years
Remuneration will be commensurate with the candidate’s qualifications and experience.
Interested applicants are welcome to apply here and/or email Associate Professor Thomas Yeo at email@example.com with a cover letter, resume, and contacts of two-three references. Only shortlisted candidates will be notified.
At NUS, the health and safety of our staff and students are one of our utmost priorities, and COVID-vaccination supports our commitment to ensure the safety of our community and to make NUS as safe and welcoming as possible. Many of our roles require a significant amount of physical interactions with students/staff/public members. Even for job roles that may be performed remotely, there will be instances where on-campus presence is required.
Taking into consideration the health and well-being of our staff and students and to better protect everyone in the campus, applicants are strongly encouraged to have themselves fully COVID-19 vaccinated to secure successful employment with NUS.
Location: Kent Ridge Campus
Organization: Yong Loo Lin School of Medicine
Department : Dean's Office (Medicine)
Employee Referral Eligible: No
Job requisition ID : 17967